Розробка інтелектуальної системи підтримки для вибору лікування гепатоцелюлярної карциноми

The object of the study is the clinical decision-making process for selecting of hepatocellular carcinoma (HCC) treatment method based on the patient's medical data. The process of the HCC treatment method selection remains poorly formalized and is characterized by multi-criteria and the presence of numerous clinical situations, for each of which it is necessary to promptly identify the most accurate therapeutic solution. This study develops an intelligent medical decision support system for HCC treatment method selection based on knowledge applicable in clinical practice. It offers architectural and functional principles of the intelligent decision support system, classifying clinical situations by HCC treatment method, consisting of multiple possible combinations of 44 informative parameters. Based on the current values of these parameters, expert knowledge is transformed into production rules identifying HCC treatment methods. A heuristic procedure treatment selection is developed based on production rule analysis in accordance with current parameter values, reproducing the reasoning patterns of participants in a multidisciplinary council during their consensus decision-making process regarding HCC treatment appointment. A software implementation of a decision-making model for HCC treatment selection, implemented in C# using the Visual Study 2019 platform, enabled the integration of an intelligent system with web technologies. The intelligent medical decision support system automates the unique experience of professionals and helps physicians in a multidisciplinary consultation make prompt and informed decisions online regarding the appointment of personalized therapy. The system was piloted with expert physicians in several iterations until complete match between the consensus decision of the multidisciplinary council and the decision made by the developed system in accordance with clinical recommendations was achieved

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Journal
The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy
Published
2025-12-30
Primary Topic
Artificial Intelligence and Decision Support Systems
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article
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article

Розробка інтелектуальної системи підтримки для вибору лікування гепатоцелюлярної карциноми

Nuru Bayramov, Masuma Mammadovа, Zarifa Jabrayilova, M. Kh. Huseynova et al.
The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy
Artificial Intelligence and Decision Support Systems
article

Розробка інтелектуальної системи підтримки для вибору лікування гепатоцелюлярної карциноми

Nuru Bayramov, Masuma Mammadovа, Zarifa Jabrayilova, M. Kh. Huseynova, Tetyana Baydyk
article en

Abstract

The object of the study is the clinical decision-making process for selecting of hepatocellular carcinoma (HCC) treatment method based on the patient's medical data. The process of the HCC treatment method selection remains poorly formalized and is characterized by multi-criteria and the presence of numerous clinical situations, for each of which it is necessary to promptly identify the most accurate therapeutic solution. This study develops an intelligent medical decision support system for HCC treatment method selection based on knowledge applicable in clinical practice. It offers architectural and functional principles of the intelligent decision support system, classifying clinical situations by HCC treatment method, consisting of multiple possible combinations of 44 informative parameters. Based on the current values of these parameters, expert knowledge is transformed into production rules identifying HCC treatment methods. A heuristic procedure treatment selection is developed based on production rule analysis in accordance with current parameter values, reproducing the reasoning patterns of participants in a multidisciplinary council during their consensus decision-making process regarding HCC treatment appointment. A software implementation of a decision-making model for HCC treatment selection, implemented in C# using the Visual Study 2019 platform, enabled the integration of an intelligent system with web technologies. The intelligent medical decision support system automates the unique experience of professionals and helps physicians in a multidisciplinary consultation make prompt and informed decisions online regarding the appointment of personalized therapy. The system was piloted with expert physicians in several iterations until complete match between the consensus decision of the multidisciplinary council and the decision made by the developed system in accordance with clinical recommendations was achieved

The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy
Azerbaijan Medical University (AZ), Universidad Nacional Autónoma de México (MX)
Peace, Justice and strong institutions
Openalex Percentile: Top 21%
Artificial Intelligence and Decision Support Systems
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